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Mainlobe Interference Suppression Based on POL-SPICE and Covariance Matrix Reconstruction for Polarization-Sensitive

Buma Xiao¹, Huafeng He¹, Liyuan Wang¹

¹College of Missile Engineering, Rocket Force Engineering University, Xi'an 710025, China.

Sensors (Basel, Switzerland)

|May 13, 2026

Summary

This study introduces a novel method for suppressing mainlobe interference in adaptive beamforming. The technique preserves mainlobe shape and improves performance, even with desired signals and multiple interferences present.

Keywords:

covariance matrix reconstruction joint spatial–polarization domain beamforming mainlobe interference suppression sparse iterative covariance-based estimation

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Area of Science:

Signal Processing
Electromagnetics
Array Signal Processing

Background:

Adaptive beamforming with polarization-sensitive arrays offers spatial-polarization filtering for interference suppression.
Mainlobe distortion and performance degradation arise when desired signals or multiple interferences coexist with the mainlobe.

Purpose of the Study:

To propose an advanced mainlobe interference suppression method for adaptive beamforming.
To address performance limitations caused by desired signals and multiple mainlobe interferences.

Main Methods:

Utilizing Polarimetric Sparse Iterative Covariance-based Estimation (POL-SPICE) for accurate parameter estimation (DOA, polarization, power).
Reconstructing the covariance matrix by nulling source power.
Constructing a feature projection matrix for signal preprocessing.

Main Results:

The proposed method effectively eliminates the impact of desired signals and mainlobe interferences on beamforming.
Achieved successful interference suppression while preserving mainlobe shape.
Demonstrated applicability in complex scenarios with desired signals and multiple interferences.

Conclusions:

The POL-SPICE and covariance matrix reconstruction method enhances adaptive beamforming performance.
The technique offers superior interference suppression and mainlobe preservation compared to existing methods.
Validated for scenarios involving coexistence of desired signals and multiple mainlobe interferences.